The purpose of this paper is to compare and analyze the determinants of agricultural income by quantile through quantile regression considering the heterogeneous distribution of agricultural income of returning farmers. Unlike OLS of the mean concept, quantile regression is an analysis method that can consider the entire distribution, including each quantile. In this study, the 25th, 50th, and 75th quartiles were analyzed and compared to each other and they were compared with the OLS result. The results showed that 15 factors in the OLS result, 4 factors in the 25th quartile, 9 factors in the 50th quartile, and 14 factors in the 75th quartile were found to have a statistically significant effect. This can leads to a conclusion that the OLS result, which is based on the average concept, was relatively more influenced by high quantiles such as the 75th quartile. In other words, this implies that the characteristics of low-income return farmers were relatively less reflected. The magnitude of the influence also showed a similar tendency to increase with higher quantiles.